Fuzzy Evidence Theoretic Approaches for Knowledge Discovery in Spatial Uncertainty Data Sets

Although uncertainties exist in spatial knowledge discovery, they have not been paid much attention to. In the past years, the most researches of spatial knowledge discovery focused on the methods of data mining and its algorithms. In this paper, uncertainty and its propagation of spatial data are discussed and analysed firstly. Then, uncertainties at various stages of spatial knowledge discovery are briefly analysed, including data selection, data preprocessing, data mining, knowledge representation and uncertain reasoning. Thirdly, a method of spatial knowledge discovery in conjunction with uncertain reasoning by means of fuzzy evidence theory is proposed. Herein, the framework for uncertainty handling in spatial knowledge discovery is constructed, and the fundamental issues include soft discretization of spatial data, fuzzy transformation between quantitative data and qualitative concept, reasoning under uncertainty and uncertain knowledge representation.